What are the crime patterns in neighborhoods or areas of interest?
It is challenging to get useful answers to this type of question.
Crime incidence data by location/address are often difficult or not possible to obtain.
Even where the location-based crime data are available, the data must be geocoded, e.g., assigned a census block code to each address.
Separately demographic-economic must be organized to examine contextually with the crime data.

Crime Data Analytics. Use the Crime Incidence and Socioeconomic Patterns
GIS project and associated
datasets to explore relationships between crime and small area demographic-economic characteristics.
Follow the steps described below in this section to study patterns and relationships in Kansas City and/or use this framework
to develop similar data analytics for other areas.

Framework for a case study. 409 of Missouri's 4,506 block groups are within the
jurisdiction of the Kansas City police department (KCPD) and had one or more crimes in 2014 (latest fully reported year).
There were approximately 10,400 crimes recorded by the KCPD in 2014, in the city area spanning four counties.
In this section tools and data are used to examine crime patterns in Kansas City, MO.
Crime data are included as markers/locations in a GIS project.
Crime data are also aggregated to the census block level and examined as summary data
(aggregate crimes by census block).
Crime data are related to
American Community Survey (ACS) 2014 5-year demographic-economic data
at the block group geographic level.

To perform these types of analyses, it is important to start with location-based crime data that have been attributed with type of offense (offense code).
Ideally, each crime incidence data record includes minimally
the offense code
and address of the crime.
Such location-based crime incidence data have been acquired from the KCPD.
These data are used to develop a shapefile that can be included in a
GIS project.

Patterns of Crime Incidence in Kansas City, MO
The following graphic shows patterns of crime incidence by census block for the "Plaza Area" within Kansas city.
This view shows all types of crimes aggregated to the census block level. Crimes committed where a handgun was involved are shown as black/red circular markers.
Click the graphic for a larger view that shows legend and more detail.
- View developed using CV XE GIS and related GIS project.

Patterns of Economic Prosperity & Crime Incidence
The following graphic shows patterns of economic prosperity (median household income $MHI) by
block group for the same general area as above.
This view illustrates how two types of crimes (burglary blue triangle markers and homicide (red/black square markers)
can be examined in context.
Click the graphic for a larger view that shows legend and more detail.
- View developed using CV XE GIS and related GIS project.

Data used to analyze patterns of economic prosperity/$MHI are
based on the American Community Survey (ACS) 2014 5-year estimates
at the block group geographic level.
The same scope of subject matter is available for higher level geography. The GIS project/datasets includes many types of demographic-economic subject
matter that can be used to display/analyze different socioeconomic patterns.

Using Block Group Geography/Data
Census Block Groups sit in a "mid-range" geography between census blocks and census tracts. All cover the U.S. wall-to-wall and nest together,
census blocks being the lowest common denominator for each. Block Groups (BGs) are the smallest geographic area for which
annually updated ACS 5-year estimates data are tabulated.

Advantages of using BG geodemographics include the maximum degree of geographic drill-down (using ACS data)
... enabling the most micro-perspective of demographics for a neighborhood or part of study area. A disadvantages of using BG estimates
is that typically the smaller area estimates have a relatively higher error of estimate.

ProximityOne User Group
Join the ProximityOne User Group
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Receive updates and access to tools and resources available only to members.
Use this form to join the User Group.

Support Using these Resources
Learn more about accessing and using demographic-economic data and related analytical tools.
Join us in a Data Analytics Lab session.
There is no fee for these one-hour Web sessions.
Each informal session is focused on a specific topic.
The open structure also provides for Q&A and discussion of application issues of interest to participants.

Additional Information
ProximityOne develops geodemographic-economic data and analytical tools and helps organizations knit together and use diverse data in a decision-making and analytical framework. We develop custom demographic/economic estimates and projections, develop geographic and geocoded address files, and assist with impact and geospatial analyses.
Wide-ranging organizations use our tools (software, data, methodologies) to analyze their own data integrated with other data.
Follow ProximityOne on Twitter at www.twitter.com/proximityone.
Contact us (888-364-7656) with questions about data covered in this section or to discuss
custom estimates, projections or analyses for your areas of interest.